Package: dnr 0.3.5
dnr: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family
Functions are provided to fit temporal lag models to dynamic networks. The models are build on top of exponential random graph models (ERGM) framework. There are functions for simulating or forecasting networks for future time points. Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, <doi:10.1080/10618600.2019.1594834>.
Authors:
dnr_0.3.5.tar.gz
dnr_0.3.5.zip(r-4.5)dnr_0.3.5.zip(r-4.4)dnr_0.3.5.zip(r-4.3)
dnr_0.3.5.tgz(r-4.4-any)dnr_0.3.5.tgz(r-4.3-any)
dnr_0.3.5.tar.gz(r-4.5-noble)dnr_0.3.5.tar.gz(r-4.4-noble)
dnr_0.3.5.tgz(r-4.4-emscripten)dnr_0.3.5.tgz(r-4.3-emscripten)
dnr.pdf |dnr.html✨
dnr/json (API)
| # Install 'dnr' in R: |
| install.packages('dnr', repos = c('https://abhirupkgp.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:91fcd30f8c. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-win | NOTE | Nov 23 2024 |
| R-4.5-linux | NOTE | Nov 23 2024 |
| R-4.4-win | NOTE | Nov 23 2024 |
| R-4.4-mac | NOTE | Nov 23 2024 |
| R-4.3-win | NOTE | Nov 23 2024 |
| R-4.3-mac | NOTE | Nov 23 2024 |
Exports:binaryPlotclustCoefengineEdgeengineEdgeNSengineVertexengineVertexNSexpdegntrianglesparamEdgeparamVertexparamVertexOnlyparamVertexOnlyGroupvdegree
Dependencies:abindarmbootcachemclicodacodetoolscpp11DEoptimRergmevaluatefansifastmapforeachglmnetgluehighrigraphiteratorsknitrlatticelifecyclelme4lpSolveAPImagrittrMASSMatrixmemoiseminqanetworknlmenloptrpillarpkgconfigpurrrrbibutilsRcppRcppEigenRdpackrlangrlerobustbaseshapesnastatnet.commonstringistringrsurvivaltibbletrustutf8vctrsxfunyaml
